QH9: A Quantum Hamiltonian Prediction Benchmark for QM9 Molecules

arXiv:2306.09549v4 Announce Type: replace-cross
Abstract: Supervised machine learning approaches have been increasingly used in accelerating electronic structure prediction as surrogates of first-principle computational methods, such as density functional theory (DFT). While numerous quantum chemistry datasets focus on chemical properties and atomic forces, the ability to achieve accurate and efficient prediction of the Hamiltonian matrix is highly desired, as it is the most important and fundamental physical quantity that determines the quantum states of physical systems and chemical properties. In this …

arxiv benchmark cs.ai cs.lg molecules physics.chem-ph prediction quantum type